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Mission Statement
Introduction
Credits
Ordering Info

Statistics Sequencing & Pacing Guide

AP Statistics Sequencing & Pacing Guide

Statistics Terms

Vertical Alignment

Skills Packets

Vocabulary

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© 2003 by Cobb County School District and Scantron Corporation.
All Rights Reserved.

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Cobb County School District
Mathematics (Updated July 2004)
Mathematics - Statistics
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Goals and Descriptions

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Data Analysis and Probability
 


Data Analysis and Probability

PS1: DATA ORGANIZATION: FORMULATE
The learner will be able to formulate studies to answer question to real-world situations.
  
M.STAT.1.1 Sampling: Concepts
The learner will be able to distinguish between sample and population, identify characteristics of representative samples to minimize bias and error, and recognize the variability among repeated samples taken from the same population.
Bloom's Scope Hours Source
Application Master 2.0 GA: Quality Core Curriculum, December 2000, Statistics, #8
  
M.STAT.1.2 Statistical Analysis: Estimate
The learner will be able to develop the concept of estimating population parameters using confidence intervals produced from comparisons of box plots, and apply the capture-recapture model to generate a confidence interval for the populations.
Bloom's Scope Hours Source
Application Master 3.0 GA: Quality Core Curriculum, December 2000, Statistics, #22
  
M.STAT.1.3 Statistics: Models
The learner will be able to develop estimates (both point and interval) for parameters (such as mean, standard deviation and proportion of successes) and test hypotheses concerning these parameters through the using appropriate statistical models.
Bloom's Scope Hours Source
Synthesis Master 2.0 GA: Quality Core Curriculum, December 2000, Statistics, #24
  

 

M.STAT.1.4 Sampling: \Construct
The learner will be able to construct sampling distributions from binomial populations construct student experiments, random number tables and computer simulations.
Bloom's Scope Hours Source
Analysis Master 2.0 GA: Quality Core Curriculum, December 2000, Statistics, #20
  

 

M.STAT.1.5 Mathematical Modeling: Simulation
The learner will be able to use the eight step process to build a model for simulating a given practical problem situation and use manipulatives, random number generators, calculators, and/or computers to perform the simulation to form an approximation to the problem solution.
Bloom's Scope Hours Source
Synthesis Master 8.0 GA: Quality Core Curriculum, December 2000, Statistics, #14
  

M.STAT.1.6 Sampling: Concepts
The learner will be able to understand the concept of randomness as applied to sample selection and identify other sampling methods suitable to given situations.
Bloom's Scope Hours Source
Analysis Master 1.0 GA: Quality Core Curriculum, December 2000, Statistics, #9
  

M.STAT.1.7 Data Collection: Methods
The learner will be able to design a survey or an opinion poll or choose other methods of data to solve problems.
Bloom's Scope Hours Source
Synthesis Master 1.0 GA: Quality Core Curriculum, December 2000, Statistics, #10
  
PS2: DATA ORGANIZATION: CONDUCT
The learner will be able to conduct investigations using statistical tools and display resulting data.
  
M.STAT.2.1 Data: Organize/Summarize/Characterize
The learner will be able to organize, summarize, characterize, and interpret data from practical situations using relevant data sets by constructing of tables, graphs, and charts including frequency distributions, histograms, line plots, stem-and-leaf plots, box plots, and/or scatterplots for bivariate data.
Bloom's Scope Hours Source
Synthesis Master 3.0 GA: Quality Core Curriculum, December 2000, Statistics, #1
  

 

M.STAT.2.2 Sampling: Create
The learner will be able to construct and interpret 90% and 95% box plots for various size samples, and use the box plots to summarize the sampling distribution.
Bloom's Scope Hours Source
Analysis Master 1.0 GA: Quality Core Curriculum, December 2000, Statistics, #21
  

 

M.STAT.2.3 Central Limit Theorem: Use
The learner will be able to apply the Central Limit Theorem and understand its impact on the distribution of the sample mean, including the effects of sample size.
Bloom's Scope Hours Source
Application Master 2.0 GA: Quality Core Curriculum, December 2000, Statistics, #23
  

 

M.STAT.2.4 Data Collection: Experimental
The learner will be able to collect and analyze data using experimental models and random number tables and generators.
Bloom's Scope Hours Source
Analysis Master 2.0 GA: Quality Core Curriculum, December 2000, Statistics, #11
  

 

M.STAT.2.5 Simulations: Perform
The learner will be able to perform simulations for problems where the probability of success is one-half and other then one-half and perform simulations for situations with an unknown number of key components.
Bloom's Scope Hours Source
Synthesis Master 4.0 GA: Quality Core Curriculum, December 2000, Statistics, #15
  
PS3: DATA ANALYSIS: CENTRAL TENDENCY
The learner will be able to analyze real-world data collected using appropriate measures of central tendency and dispersion.
  
M.STAT.3.1 Variation: Analyze Source
The learner will be able to analyze sources of variation and interpret and draw conclusions when solving applied problems. (Some may include the difference between samples and populations, sampling variability, the application of probability to make generalizations and predictions about populations based on the analysis of samples, the concept of random or chance variation, and analysis of variance).
Bloom's Scope Hours Source
Analysis Develop 4.0 GA: Quality Core Curriculum, December 2000, Statistics, #28
  

 

M.STAT.3.2 Data Analysis: Summarize
The learner will be able to apply the measures of central tendency (mean, median, and mode), and measures of spread ( range, interquartile range, and standard deviation).
Bloom's Scope Hours Source
Comprehension Master 1.0 GA: Quality Core Curriculum, December 2000, Statistics, #2
  

 

M.STAT.3.3 Data Analysis: Recognize/Trends
The learner will be able to identify trends in data represented graphically, including patterns, clusters, and outliers.
Bloom's Scope Hours Source
Knowledge Master 1.0 GA: Quality Core Curriculum, December 2000, Statistics, #3
  

 

M.STAT.3.4 Statistical Analysis: Alternative
The learner will be able to apply distribution-free or non-parametric methods as alternative to statistical analyses that make assumptions about populations sampled. (Applications from practical problems can be presented using such measures as the sign test, the Mann-Whitney U test and Sperman's rank correlation test).
Bloom's Scope Hours Source
Analysis Introduce 5.0 GA: Quality Core Curriculum, December 2000, Statistics, #25
  
PS4: DATA ANALYSIS: EVALUATE
The learner will be able to evaluate statistical studies and determine inferences that can be justified.
  
M.STAT.4.1 Data: Analyze Bivariate
The learner will be able to analyze bivariate data represented graphically and predict results by fitting a line to the data, using methods such as mean fit and least squares and tools such as computers and calculators.
Bloom's Scope Hours Source
Analysis Master 4.0 GA: Quality Core Curriculum, December 2000, Statistics, #4
  
M.STAT.4.2 Correlation: Compute/Investigate
The learner will be able to for a given bivariate scatter plot or data set, characterizes the correlation, calculates the correlation coefficient, and determine if a linear relationship exists.
Bloom's Scope Hours Source
Analysis Master 2.0 GA: Quality Core Curriculum, December 2000, Statistics, #5
  
M.STAT.4.3 Data: Linear Transformation
The learner will be able to understand the effect of linear transformations have on the analysis and exploration of data.
Bloom's Scope Hours Source
Analysis Master 1.0 GA: Quality Core Curriculum, December 2000, Statistics, #6
  
M.STAT.4.4 Data Analysis: Interpret Out
The learner will be able to interpret the outcome of data analysis and communicate these results.
Bloom's Scope Hours Source
Analysis Master 1.0 GA: Quality Core Curriculum, December 2000, Statistics, #12
  

M.STAT.4.5 Statistics: Proper/Improper
The learner will be able to identify sound examples of statistics in decision making and correct the misuses of statistics.
Bloom's Scope Hours Source
Analysis Master 1.0 GA: Quality Core Curriculum, December 2000, Statistics, #7
  

M.STAT.4.6 Proof: Use/Mathematical Induction
The learner will be able to use mathematical induction the derivation of certain formulas, the verification of appropriate properties, proofs of equivalence, and deductive reasoning.
Bloom's Scope Hours Source
Synthesis Introduce 2.0 GA: Quality Core Curriculum, December 2000, Statistics, #27
  
PS5: PROBABILITY: COUNTING PRINCIPLES
The learner will be able to apply counting principles in real world contexts.
  
M.STAT.5.1 Experiments: Apply Results
The learner will be able to use student-generate data sets, games of chance, manipulatives, and historic data to estimate probabilities with the empirical approach. Apply the results obtained from active experiments to illustrate the Law of Large Numbers and to develop the concept of theoretical probability.
Bloom's Scope Hours Source
Analysis Master 4.0 GA: Quality Core Curriculum, December 2000, Statistics, #13
  

M.STAT.5.2 Counting Methods: Apply
The learner will be able to apply counting techniques and calculate the probability of the union and the intersection of two events, the probability of the complement, and conditional probability.
Bloom's Scope Hours Source
Application Master 2.0 GA: Quality Core Curriculum, December 2000, Statistics, #16
  
PS6: PROBABILITY
The learner will be able to apply the laws of probability in real world contexts.
  
M.STAT.6.1 Probability: Find/Odds/For/Associated
The learner will be able to distinguish between odds for and probabilities and find the odds associated with given events.
Bloom's Scope Hours Source
Application Master 1.0 GA: Quality Core Curriculum, December 2000, Statistics, #17
  
M.STAT.6.2 Probability: Assign
The learner will be able to assigns probabilities to the outcomes of a random variable and calculate expected value.
Bloom's Scope Hours Source
Application Master 1.5 GA: Quality Core Curriculum, December 2000, Statistics, #18
  
M.STAT.6.3 Probability Distributions: Distinguish
The learner will be able to distinguishes between discrete and continuous distributions and solves problems using probability distributions, including binomial, normal, Poisson, and chi square.
Bloom's Scope Hours Source
Application Master 3.0 GA: Quality Core Curriculum, December 2000, Statistics, #19
  

 

M.STAT.6.4 Probability: Geometric
The learner will be able to use geometric probability to develop problem solving skills through experiments whose outcomes can be represented by points in a geometric region.
Bloom's Scope Hours Source
Synthesis Master 3.0 GA: Quality Core Curriculum, December 2000, Statistics, #26
  
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